The work in this Thesis analyzes the applicability of statistical and dynamical climate downscaling techniques on impact studies over the tourism and forest fires sectors, showing their merits and limitations. On the one hand, we analyze the applicability of the statistical techniques directly over the desired impact index, unlike the common practice based on downscaling individually all the former variables, with promising results. On the other hand, we establish the basis for a fair comparison between statistical and dynamical downscaled data. For this purpose, we propose the use of parameters not affected by the methods calibration process, such as indicators based on spells, and discard commonly used percentile-based indicators. Finally, we analyze the added value of dynamical downscaling techniques for increased resolution (and computationally expensive) simulations. In this sense, we find that the increment of spatial resolution does not add (statistically significant) value once their systematic biases are corrected.